1 Customer Data Hub Low Cost Fly High Sarawoot Lienpanich GloriSys Di Walsh Liverpool John Moores University Topics of Discussion Introducing LJMU CRM and the Learner Centred Services Programme Customer Data Integration The LJMU Customer Data Hub
2 LJMU CRM Programme CRM is the 2nd Part of ebusiness Suite implementation in line with Liverpool John Moores University Strategic Plan which includes the goals To achieve & sustain a reputation as an HEI that leads the sector in meeting the needs of its students & clients To provide an administrative & support service that is comparable with best-in-class service organisations The achievement of these goals is underpinned by a 5 year Development Programme with the need to manage by process and fact; To provide integration with Oracle Student System to support the Customer life cycle from initial enquiry right through to Alumni Uses TCA functionality/single unified database Learner Centred Services Project An implementation of an integrated 360 degree view of Student/Customer information for support staff and direct integrated access to relevant information and services for Students
3 LCS Phases Phase 1: Definition and analysis of the range of services and systems required to provide comprehensive learner support Phase 2:Implementation of CDH technical infrastructure and CDI (1st iteration 2 spoke systems OSS & CRM) Phase 3: Design of integrated service/systems offerings for learners and staff Phase 4: Staged implementation of solution Customer Data Integration Customer Data Integration (CDI) is the collection of processes, controls, automation, and skills necessary to standardise and integrate customer data originating from different sources.
4 Purposes of LJMU CDI To deliver a single view of the customer from multiple data sources, that anyone across the institution can use CDI ensures that all relevant business functions of LJMU have constant access to the most current and complete view of customer information available Business Drivers for LJMU CDI Movement from Student Centric strategy toward Customer Centric strategy Currently many different systems and customer touch-points Poor data quality can lead to poor decision making Focus on improving student experience
5 Single View of the LJMU s Customers Better understanding of our customers Reduction in duplicated customer information Improved business intelligence reporting Enhanced customer service and increased customer satisfaction Improved conversion (Recruitment to Admission) Applying CDI Methodology What CDI isn t? What s CDI Ecosystem? What are the options? What are the steps?
6 What CDI isn t? A CRM tool A solution to a technical problem A replacement for a data warehouse An application An analysis or business intelligence tool An operational data store The automation of a customer data model CDI Ecosystem Data Sources Billing Operational CRM ERP System Marketing Data Mart Disparate Contact Databases and Spreadsheets Service I N T E G R A T I O N S E R V I C E S Customer Data Hub CDI Admin Tool Web Services Applications Data Warehouse Data Mart Web Apps Packaged Apps Knowledge Worker
7 Core Functionalities of CDI Hub A single point of data retrieval Consistent value representation An accurate and repeatable means of merging data A repository of clean, reliable customer data Support of multiple data sources CDI Hub Styles Registry or Referencing The customer data remains on the source system and a series of pointers or data linkage details are stored physically on the CDI hub. Persistent This persists the customer data, meaning it copies the data as a physical record, serving as de-facto storage platform for centralised customer information. Hybrid Leverage aspects of the other two styles: some customer data remains on the source system while other data is housed persistently in the hub. External Service Providers This refers to third-party data service which essentially provide synchronisation, consolidation, and provisioning of customer master data as a service to their business customers.
8 Referencing Data Hub Cust Nbr Phone Nbr Name AB12345 020 377-6968 Bob Sands Opt In 0 Sales Account Nbr Name Phone Nbr 907 67345 Robert Sands 020 377-6968 Account Nbr Balance Name Email 457A816F78 1000 Rob Sands bobs@email.com Support Finance CDI Hub CDI Client ID System Key Field Key Value 1 Sales CustNBR AB12345 1 Support AccountNumber 90767345 1 Finance Billing Number 457A816F78 Persistent Data Hub Sales Support Finance CDI Hub CDI Client Cust Nbr Phone Nbr Billing Nbr Name AB12345 020 849201 Balance Opt In 457A816F78 Robert Sands 1000 0
9 CDI Implementation Framework 1 2 3 4 5 6 Identify Verify and Data Integration Integration Deploy CDI Data Validate Analysis Design Development Solution Requirement CDI Output Business IT Business/IT Business/IT Business/IT IT How the data will be accessed and used by applications When data should be pulled from its sources How to pull data off the various data sources will be performed by the sources themselves How to change the data representation to match the CDI Standards How to get and match data from multiple locations How to evaluate the best source Ensure that the data is accurate reflection of the context for usage Ensure that business users agree to the contents initial CDI client application link to the CDI system and pull its customer data LJMU Customer Data Hub Options and Strategy Implementation Challenges
10 From Customer Database to CDH Customer Data Hub Manage, then, publish Sourcing data Migrate, then, integrate Define Life Cycle and source of truth Customer Database Customer Life Cycle Alumni B2B Recruitment Student Enrolment Graduation Discontinuation
11 Initial Master Data Selection Strategy Option 1: CDH is a clone from the cleanest system (OSS) Option 2: Fresh installation of 11i.10.2 with initial import from OSS Implementation Tools Activities Define Life Cycle and source of truth Sourcing data Migrate, then, integrate Manage, then, publish Tools SST/SSM/DQM Customer Data Librarian Data Acquisition Customer Data Librarian and Middleware Customer Online, Portal
12 LJMU Referencing CDH CODA (Non-Oracle) Portfolio (Non-Oracle) Aleph (Non-Oracle) CODA Cust ID Portfolio Student ID Library Student ID Fusion Middleware Source Master Data Reference ** CDH Master Data Excel Import Alumni Integration Repositories Party ID OSS (Alumni) OSS (Current Students) CRM (B2B) Customer Online View
13 Topology CRM 10gAS Integration OSS istudio CDH Data Quality Process Match and Merge Reconcile and combine data based on business rules. Deploy Populates or inform the customer data hub with the resulting records. Standardise Transform and Correct data. Define Understand the data required to answer business needs Profile Analyse, characterise, and compare the content Locate Locate and validate the correct data sources.
14 Project Plan M1 M1 M2 M2 M3 M3 1. Infrastructure (3 Wk) 2. System Setup (1-2 2 Wk) 4. MW Development (2-3 3 Wk) 3a. Student Data Cleanse and Import Preparation 3b. Recruitment Data Cleanse and Import Preparation 5. Imports (2 Wk) 6. DQM (2 Wk) 7. UAT (1 Wk) 8. LIVE System Migration Patchsets Baseline for CDH Installation 11.5.10 CU2 on Oracle 10g Database 11i10 Financials Family Pack G 11i.FIN_PF.G (3653484) HZ.N (3618299) IMC.M (4017594)
15 Middleware Requirements OAS 10g B13170, B13171, B13172, and B13173 OAS Interconnect 10g Server B15128 OAS Interconnect 10g istudio B15037 OAS Metadata Repository Creation Assistant B15061 The Five Challenges 1. The Need for a Different Development Framework The well-worn, requirement-driven business intelligence and data warehouse development method won t work for CDI. 2. Stakeholder Enlistment Education (what CDI means and how the University will benefits from a CDI effort) Scenario building (picture of desired outcome ) Politics 3. Operational Data Must be Available Ensuring that the system is always up and available, that it s delivering on its intended functionality.
16 The Five Challenges 4. Nonexistent Metadata It s essential that CDI implementations consider metadata an implementation priority. It allows data librarian to establish and control for data definitions and rules for consistency and accuracy, and provide a baseline for data validation and certification. 5. Data Quality It s a continuous process of monitoring and managing the data Data owners must be appointed Summary Customer meta-data, life cycle, and data quality management are the keys Don t be too excited about the technology It is the processes and disciplines
17 sarawoot@glorisys.com d.m.walsh@ljmu.ac.uk g.philip@ljmu.ac.uk